open_spiel
AirSim
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open_spiel | AirSim | |
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44 | 10 | |
3,989 | 15,844 | |
1.2% | 1.1% | |
9.4 | 0.0 | |
9 days ago | 13 days ago | |
C++ | C++ | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
open_spiel
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What projects or open-source contributions can impress Jane Street recruiters for a Quant SWE role ?
Deep mind actually has a repository where they applied this algorithm for incomplete-knowledge games. You could use it for reference: https://github.com/deepmind/open_spiel/tree/master/open_spiel/python/algorithms
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I want to build a learning agent for a combinatorial game
+1. You can also find an implementation of Clobber and AlphaZero (and many other basic RL algorithms) in OpenSpiel: https://github.com/deepmind/open_spiel
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minimax for imperfect-information turn-games?
You can find a lot of code online if you look, and many of these applied to Poker. There's a general implementation of both in Python and C++ in OpenSpiel, with some examples applied to small poker games. It's nice code to learn from because the algorithms operate over generic game descriptions, so there aren't game-specific design choices mixed up with the implementation of the algorithms, and you can create your own poker game and just run them on it.
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OpenSpiel 1.3 Released!
And many other additions and improvements. See all the details here: https://github.com/deepmind/open_spiel/releases/tag/v1.3
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What's a good OpenAI Gym Environment for applying centralized multi-agent learning using expected SARSA with tile coding?
I would checkout the openspiel package. It's main focus is RL in games (multi-agent environments). You'll find RL examples there and games that are small enough to solve without deep RL. There's also a wide range of environments from fully cooperative to adversarial zero-sum.
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Competitive reinforcement learning for turn-based games
Hi, you can check out OpenSpiel: https://github.com/deepmind/open_spiel/
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Reinforcement learning and Game Theory a turn-based game
as for algorithms , openspiel repository has few implementations some of these are not related to imperfect information games , and others are not for multiagent environment and others are tabular algorithms .
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Shimmy 1.0: Gymnasium & PettingZoo bindings for popular external RL environments
This includes single-agent Gymnasium wrappers for DM Control, DM Lab, Behavior Suite, Arcade Learning Environment, OpenAI Gym V21 & V26. Multi-agent PettingZoo wrappers support DM Control Soccer, OpenSpiel and Melting Pot. For more information, read the release notes here:
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How to deal with situations where the RL agent cannot act at every time step?
I've had some success using Action Masking - you can refer to here https://github.com/deepmind/open_spiel/blob/120420a74a69354d64c10b51cd129d4587f9f325/open_spiel/python/algorithms/dqn.py but for DQN you need to mask out q values for invalid actions (as well as masking them during prediction). In my case I'm able to place my mask in the observation so can fetch it quite easily during prediction but if that's not possible you could query it from the environment and store it in the replay buffer (like they do in the link I shared)
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How to search the game tree with depth-first search?
Take a look at this simple implementation: https://github.com/deepmind/open_spiel/blob/master/open_spiel/algorithms/minimax.cc
AirSim
- Modding API for old game: Strategies to ensure it runs on older systems while not losing productivity?
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Replay system (gamemode from c++)
Have created all widgets, code compile successfully but have problem with replay spectator. Im using plugin AirSim https://github.com/microsoft/AirSim it is plugin that simulate drone. It has own gamemode AirsimGamemode (here is c++ file https://github.com/microsoft/AirSim/tree/main/Unreal/Plugins/AirSim/Source) that spawn drone at start. Problem is that I cant assign BP_PC_Spectator there. So I created own gamemode that I thought will override AirSimGameMode. It kinda did, it spawned drone on start but replay spectator widget show record screen, but it is not shown on play replay screen and I cannot move there as well.
- Heat map of environment monitored by drone
- 3D heatmap of environment monitored by drone
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Airsim, ROS, can msg be shared between packages/nodes ?
Hi, I implemented path planner as node in ROS. Now I want to try the route planner in the AirSim simulator. During path execution, I want to get outputs from sensors such as GPS, IMU and Lidar. AirSim come with build in wrapper (https://github.com/microsoft/AirSim/tree/main/ros/src/airsim_ros_pkgs) that create topic and services once launched. Wrapper create two nodes, one to obtain sensors data and one to control drone. Wrapper is build in AirSim directory and path planer is in another. Is it possible to share msg so I can call and subscribe to wrapper topics in my planner node ? Or do I have to write msg for every topic, service I want to use ?
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Destruction of a russian fuel truck
And there are also some open-source projects you could join, instead of starting a new one. This one looks interesting, haven't tried it though: https://github.com/Microsoft/AirSim
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What happened in IoT last two months? Here are some headlines I found interesting
In 2017 Microsoft created AirSim, an open-source simulation platform for AI research and experimentation with drones and cars. This July, Microsoft announced the upcoming release of a new simulation platform and the archive of the original 2017 AirSim.
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Currently writing out a plan for an RL based path-planning project. (I'm doing it for my Smart Vehicles course in my Master's Degree) Don't have much domain knowledge atm but looking for some advice on how to approach the problem?
AirSim: https://github.com/microsoft/AirSim
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8+ Reinforcement Learning Project Ideas
AirSim
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Is it possible to train a self driving car on google colab?
I've been trying for a while now and I started thinking it may not be possible. If anyone has managed to train a self-driving car simulator using openai gym on google colab(preferably), or on any remote server (AWS, GCP, ...) please let me know. So far, I tried carla, airsim, svl, deepdrive and they are all equally useless unless run locally with a gui. I'd really appreciate if someone suggests some way that actually can make it possible.
What are some alternatives?
muzero-general - MuZero
carla - Open-source simulator for autonomous driving research.
PettingZoo - An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
ml-agents - The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
gym - A toolkit for developing and comparing reinforcement learning algorithms.
rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.
GAAS - GAAS is an open-source program designed for fully autonomous VTOL(a.k.a flying cars) and drones. GAAS stands for Generalized Autonomy Aviation System.
gym-battleship - Battleship environment for reinforcement learning tasks
Autonomous-Ai-drone-scripts - State of the art autonomous navigation scripts using Ai, Computer Vision, Lidar and GPS to control an arducopter based quad copter.
TexasHoldemSolverJava - A Java implemented Texas holdem and short deck Solver
apollo - An open autonomous driving platform